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SQL - How to get Count, Group by based on Like Message
Below query will execute a Table of records with Error, Error Types and its count.
I have to group by further based on Like messages in the ErrorType Column.
How should i do that.
I have to group by further based on Like messages in the ErrorType Column.
How should i do that.
create table #t
(
BillId int,
StepName varchar(100),
StepExec varchar(100),
StepExecResult varchar(100),
Created_date datetime
)
insert into #t
values
(1, 'Initiated', 'Taken Place','Pass', getdate()-10),
(1, 'POS', 'Deadlock Error','Error', getdate()-9),
(1, 'POS', 'Processed','Pass', getdate()-9),
(1, 'Merchandise', 'Taken Place','Pass', getdate()-8),
(1, 'verification', 'Webservice call error','Error', getdate()-7),
(1, 'verification', 'Webservice call error','Error', getdate()-6),
(1, 'verification', 'Webservice call','Pass', getdate()-5),
(1, 'verification', 'Webservice Response','Error', getdate()-5),
(1, 'verification', 'Webservice Response','Pass', getdate()-5),
(1, 'verification', 'Timeout Error','Error', getdate()-5),
(1, 'verification', 'Timeout Error','Error', getdate()-5),
(1, 'verification', 'Timeout Error','Error', getdate()-5),
(1, 'verification', '','Pass', getdate()-5),
(1, 'Payment', 'calculationError','Error', getdate()-4),
(1, 'Payment', 'calculationProcessed','Pass', getdate()-3),
(1, 'Completed', 'Archived','Pass', getdate()-1),
(2, 'Initiated', 'Taken Place','Pass', getdate()-10),
(2, 'POS', 'Deadlock Error','Error', getdate()-9),
(2, 'POS', 'Processed','Pass', getdate()-9),
(2, 'Merchandise', 'Taken Place','Pass', getdate()-8),
(2, 'verification', 'Webservice call error on 07/23/2016','Error', getdate()-7),
(2, 'verification', 'Webservice call error on 07/24/2016','Error', getdate()-6),
(2, 'verification', 'Webservice call','Pass', getdate()-5),
(2, 'verification', 'Webservice Response','Error', getdate()-5),
(2, 'verification', 'Webservice Response','Pass', getdate()-5),
(2, 'verification', '','Pass', getdate()-5),
(2, 'Payment', 'calculationProcessed','Pass', getdate()-3),
(2, 'Completed', 'Archived','Pass', getdate()-1)
select
stepname, count(*) as ErrorCount
from
#t
where
StepExecResult = 'Error'
group by
stepname
SELECT StepName ,
SUM(COUNT(DISTINCT BillId)) OVER (PARTITION BY StepName) TotalStepError,
StepExec ,
COUNT(DISTINCT BillId) ErrorTypeCount
FROM #t
WHERE StepExecResult = 'Error'
GROUP BY StepName,
StepExec
StepName TotalStepError StepExec ErrorTypeCount
----------------------------------------------------------------
Payment 1 calculationError 1
POS 2 Deadlock Error 2
verification 6 Timeout Error 1
verification 6 Webservice call error 3
verification 6 Webservice Response 2
Who is Participating?
"conditional aggregates" use a case expression INSIDE the aggregation function
COUNT( case when ErrorType like 'webservice%' then ErrorType end )
note: count only increments for a non-null value so don't count and provided a non-null else condition
e.g. alternatives are:
COUNT( case when ErrorType like 'webservice%' then 1 else NULL end )
SUM( case when ErrorType like 'webservice%' then 1 else 0 end )
Personally I prefer to use COUNT() instead of SUM() for this.
COUNT( case when ErrorType like 'webservice%' then ErrorType end )
note: count only increments for a non-null value so don't count and provided a non-null else condition
e.g. alternatives are:
COUNT( case when ErrorType like 'webservice%' then 1 else NULL end )
SUM( case when ErrorType like 'webservice%' then 1 else 0 end )
Personally I prefer to use COUNT() instead of SUM() for this.
Thanks Paul. But Error Type like .. will not be always Webservice. In my production data, I have around 100 different types of error. Almost 70% of errors have date time on it. So when i run the count, group by query .. it distinct the error based on date time also.
I did not expect one example to cover all your needs.
What is "the expected result" from you sample data?
If you don't want rows by date/time use max(datetimecolumn) or min() depending on what you want.
Or perhaps
group by cast(datetimecol as date)
This would give rows by date only without time of day
What is "the expected result" from you sample data?
If you don't want rows by date/time use max(datetimecolumn) or min() depending on what you want.
Or perhaps
group by cast(datetimecol as date)
This would give rows by date only without time of day
I think , It has to be some thing like this. I have created a Temp table with Like Type messages.
create table #t
(Stepname varchar(100),
TotalStepError int,
StepExec nvarchar(1000),
ErrorTypeCount int
)
insert into #t values
('Payment',1,'calculationError',1),
('POS', 2, 'Deadlock Error on 07/21/2016', 1),
('POS', 2, 'Deadlock Error on 07/22/2016', 1),
('verification', 6, 'Timeout Error', 1),
('verification', 6, 'Webservice call error', 1),
('verification', 6, 'Webservice call error on 07/23/2016', 1),
('verification', 6, 'Webservice call error on 07/24/2016', 1),
('verification', 6, 'Webservice Response', 2)
select * from #t
-- This is based on Like Type
Create Table #ErrorLikeType
(
TypeLike varchar(1000)
)
Insert into #ErrorLikeType values
('Webservice call error'),
('Timeout error')
select * from #ErrorLikeType
--Expected Result - I have to write some kind of relation between my Temp Table and Like type table.
Stepname TotalStepError StepExec ErrorTypeCount
---------------------------------------------------------------------------------
Payment 1 calculationError 1
POS 2 Deadlock Error 2
verification 6 Timeout Error 1
verification 6 Webservice call error 3
verification 6 Webservice Response 2
Why did you change the structure of your #t table?
I have originally made this query, but now it does not work with your new #t structure. Anyway, here is the query:
I have originally made this query, but now it does not work with your new #t structure. Anyway, here is the query:
SELECT StepName ,
SUM(COUNT(DISTINCT BillId)) OVER (PARTITION BY StepName) TotalStepError,
e.TypeLike ,
COUNT(DISTINCT BillId) ErrorTypeCount
FROM #t t left join #ErrorLikeType e on t.StepExec like e.TypeLike + '%'
WHERE StepExecResult = 'Error'
GROUP BY StepName,
e.TypeLike
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Original table:
Open in new window
New table:
Open in new window
But anyway, you'll figure out how to adjust the query